It All Starts with the Data
The foundation of any AI project—whether targeted in scope or aimed at company-wide transformation—is a robust data strategy and governance framework. We will audit the current state of your data structures and pipelines.
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Do you have the sources and licences in place that fit your needs ?
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Do you have a clear vision of data versioning and lineage ?
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Does the schema alignment allow communication between systems ?
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Are your metadata complete ?
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What are your processes for data quality and bias prevention ?
These are some of the key points we will review with you.
We will also help you setting up an efficient storage solution if not already in place.
Megalith's 5 Steps to Success
Click each step number for details
Clearly Define
the Objectives
Solution Development
Setup Continuous
Improvement
AI Readiness Assessment
Progressive
Deployment
Scope & use case(s) validation
Go/No Go
Solution Validation by Client
Timelines given below are indicative and subject to adjustment depending on project scope
1
Clearly Define Objectives
1 month
Upon agreement to enter a collaboration, we spend time with you to review the Key Performance Indicators you are the most keen to boost in one or more departments, and flesh out a preselection of the corresponding AI use cases.
We can also map out a full organizational transformation for longitudinal AI integration if this is what you envision.
Once we have verified our aligned understanding of the scope and your desired outcomes, we can proceed to a more in-depth evaluation of your current status, assets and bottlenecks in Step 2.
2
AI Readiness Assessment
2-3 months
At this stage we will review all key elements which condition the feasibility of the previously defined objectives:
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Data audit: We will inventory all current internal and external data sources, assess their quality, review the metadata, the ontologies and integration points
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Technology and infrastructure review : this is where we investigate your data storage and pipelines, compute power, your current APIs and models if you have some in place
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Governance and security assessment, review of all workflows
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Mapping of all your relevant roles and internal availability of the necessary skills and experience
From there we will perform a gap analysis, draw a more detailed roadmap and formulate recommendation for the overarching strategy. We will hierarchize the realistic use case by expected ROI/impact and list possible solution types in a report. You will get a budget estimate for the following steps.
This is the first checkpoint in the process, Go/No Go decision by the client with validation on which use cases to pursue. Our intervention may end here if you'd like to make some progress alone, and resume later when you are ready.
3
Solution Development
4-6 months
At the beginning of this phase, a formal joint team is assembled with your project owner and key contributors together with our project leader, managers and experts. A charter is created and we initiate a rhythm of weekly meetings with steady and tangible progress in mind without overloading your team.
We will impulse and guide the work, and perform ourselves the tasks whenever possible. The major deliverables for step 3 are :
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Implement all the missing foundational elements that were identified in the gap analysis, including new licenses for important data sources (limited access at first to avoid expenses, for testing purposes)
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Select candidate solutions, execute pilots (models training and hyperparameter tuning if relevant) and comparative performance testing
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Validate output quality and user experience with a subgroup of your users
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Come up with a scalability plan
We reach the second intermediate checkpoint before full execution of the project, we will fully deploy upon your validation the final selected (set of) solution(s) at the operational scale.
4
Progressive Deployment
3-4 months
During that phase we will ensure that everything is ready for your organization to use the new capabilities routinely and reach the KPI targets. Intermediate scales/scopes for iterated deployment are often used to integrate the solution(s) within the existing systems of the company.
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A change management task force is established
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The new governance model and processes are rolled out, adequate training is carried out for the different user groups and documentation is available
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The production pipelines are put in place with monitoring tools covering data quality, performance, bias, drift... APIs and data flows are standardized, licenses and compute power are upgraded as necessary.
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Validation against relevant regulatory frameworks is performed. It is key to ensure audit trails and explainability reports are produced regularly.
5
Setup Continuous Improvement
2 months
This is the final stage, ensuring you will be able to fly with your own wings !
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Automated monitoring and reporting is in place for all key aspects of performance
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Plans and periodicity for training data refreshing and model retraining are defined
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An AI Center of Excellence is established in your organization
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A roadmap for possible future improvements and expansions of your AI capabilities is created
Senior Management will be invited to a workshop to assimilate how to leverage the new capabilities for decision-making, how to foster a culture of continuous innovation and education in the field, important metrics to monitor and how to plan for the future.
